Maize root distributions strongly associated with water tables in Iowa, USA
Maize root distributions strongly associated with water tables in Iowa, USA
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DOI：
10.1007/s11104-019-04269-6
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发表时间：
2019-11-01
期刊：
影响因子：
4.9
通讯作者：
Archontoulis, Sotirios, V
中科院分区：
文献类型：
--
作者：
Nichols, Virginia A.;Ordonez, Raziel A.;Archontoulis, Sotirios, V
根系分布决定作物养分吸收和土壤碳输入模式。迄今为止，根系分布数据很少，但需要提高知识和预测种植系统的可持续性。在这项研究中，我们试图（i）量化玉米（玉米）和大豆（大豆）根的深度和环境在美国爱荷华州的变化和（ii）确定环境因素解释最多的变化。方法在三年多的时间里，我们收集了16个玉米和12个大豆田间试验在灌浆0至210厘米的土芯。根质量，长度，碳（C）和氮（N）的确定在30厘米的增量，再加上作物，土壤，管理和天气相关的测量。结果玉米和大豆根系中，根质量分布在30 cm以上的比例分别为52%~ 94%和54%~ 84%。玉米根系分布的变化与地下水位的深度密切相关，大豆根系分布的变化与土壤物理属性密切相关。根部C：N比变化很大，没有深度模式，大豆和玉米的平均C：N比分别为20和30。在这两种作物中，比根长随深度增加到60厘米，此后保持不变。结论：根系的实地研究应考虑地下水位和土壤水分测量的深度，因为它们会影响根系的垂直分布。
Aims Root distributions determine crop nutrient access and soil carbon input patterns. To date, root distribution data are rare but needed to improve knowledge and prediction of cropping system sustainability. In this study, we sought to (i) quantify variation in maize (Zea mays) and soybean (Glycine max) roots by depth and environment across Iowa, USA and (ii) identify environmental factors explaining the most variation. Methodology Over three years we collected soil cores from 0 to 210 cm in 16 maize and 12 soybean field experiments at grain filling. Root mass, length, carbon (C) and nitrogen (N) were determined at 30 cm increments, coupled with crop, soil, management, and weather-related measurements. Results Percentage of root mass located in the top 30 cm varied from 52 to 94% in maize and 54-84% in soybean. Variation in maize root distributions was strongly associated with depth to water tables, variation in soybean with soil physical attributes. Root C:N ratios were highly variable with no depth-pattern, averaging 20 and 30 for soybean and maize, respectively. In both crops, specific root lengths increased with depth to 60 cm, and thereafter remained constant. Conclusions Field studies of roots should consider depth to water tables and soil moisture measurements, as they influence vertical root distributions.